Genome-Wide Prediction Methods in Highly Diverse and Heterozygous Species: Proof-of-Concept through Simulation in Grapevine

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.     

Confrontation of cryptic diversity and mate discrimination within Gammarus pulex and Gammarus fossarum species complexes

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Free mRNA in excess upon polysome dissociation is a scaffold for protein multimerization to form stress granules

The sequence of events leading to stress granule assembly in stressed cells remains elusive. We show here, using isotope labeling and ion microprobe, that proportionally more RNA than proteins are present in stress granules than in surrounding cytoplasm. We further demonstrate that the delivery of single strand polynucleotides, mRNA and ssDNA, to the cytoplasm can trigger stress granule assembly. On the other hand, increasing the cytoplasmic level of mRNA-binding proteins like YB-1 can directly prevent the aggregation of mRNA by forming isolated mRNPs, as evidenced by atomic force microscopy. Interestingly, we also discovered that enucleated cells do form stress granules, demonstrating that the translocation to the cytoplasm of nuclear prion-like RNA-binding proteins like TIA-1 is dispensable for stress granule assembly. The results lead to an alternative view on stress granule formation based on the following sequence of events: after the massive dissociation of polysomes during stress, mRNA-stabilizing proteins like YB-1 are outnumbered by the burst of nonpolysomal mRNA. mRNA freed of ribosomes thus becomes accessible to mRNA-binding aggregation-prone proteins or misfolded proteins, which induces stress granule formation. Within the frame of this model, the shuttling of nuclear mRNA-stabilizing proteins to the cytoplasm could dissociate stress granules or prevent their assembly.     

Solution properties of an exopolysaccharide from a Pseudomonas strain obtained using glycerol as sole carbon source

We report the solution properties of a new exopolysaccharide (EPS) obtained from a Pseudomonas strain fed with glycerol as the sole source of carbon. This high molecular mass (3 × 10⁶ g mol⁻¹) biopolymer is essentially made of galactose monomers with pyruvate and succinate groups imparting a polyelectrolyte character. The Smidsrod parameter B computed from the ionic strength dependence of the intrinsic viscosity indicates that the EPS backbone is rather flexible. In salt free aqueous solutions, the zero shear viscosity scaling with concentration follows a typical polyelectrolyte behavior in bad solvent, whereas at high ionic strength the rheological response is reminiscent from neutral polymers. Light scattering data indicate that the EPS adopts a globular conformation as a result of hydrophobic interactions. EPS solutions are stable within 4 days as particle sizing does not indicate EPS aggregation. Both globular conformation and stability against precipitation from solution are attributed to the low charge density of the polyelectrolyte.     

VARIATION BETWEEN POPULATIONS AND LOCAL ADAPTATION IN ACANTHOCEPHALAN‐INDUCED PARASITE MANIPULATION

Many trophically transmitted parasites manipulate their intermediate host phenotype, resulting in higher transmission to the final host. However, it is not known if manipulation is a fixed adaptation of the parasite or a dynamic process upon which selection still acts. In particular, local adaptation has never been tested in manipulating parasites. In this study, using experimental infections between six populations of the acanthocephalan parasite Pomphorhynchus laevis and its amphipod host Gammarus pulex, we investigated whether a manipulative parasite may be locally adapted to its host. We compared adaptation patterns for infectivity and manipulative ability. We first found a negative effect of all parasite infections on host survival. Both parasite and host origins influenced infection success. We found a tendency for higher infectivity in sympatric versus allopatric combinations, but detailed analyses revealed significant differences for two populations only. Conversely, no pattern of local adaptation was found for behavioral manipulation, but manipulation ability varied among parasite origins. This suggests that parasites may adapt their investment in behavioral manipulation according to some of their host's characteristics. In addition, all naturally infected host populations were less sensitive to parasite manipulation compared to a naive host population, suggesting that hosts may evolve a general resistance to manipulation.     

Genetic risk factors for BMI and obesity in an ethnically diverse population: Results from the population architecture using genomics and epidemiology (PAGE) study

Objective:

Several genome–wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups.

Design and Methods:

As part of the “Population Architecture using Genomics and Epidemiology (PAGE)” Consortium, we investigated the association between 13 GWAS‐identified single‐nucleotide polymorphisms (SNPs) and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African‐Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI‐increasing allele of each SNP, we calculated β coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI ≥ 30) followed by fixed‐effects meta‐analysis to combine results across PAGE sites. Analyses stratified by racial/ethnic group assumed an additive genetic model and were adjusted for age, sex, and current smoking. We defined “replicating SNPs” (in European Americans) and “generalizing SNPs” (in other racial/ethnic groups) as those associated with an allele frequency‐specific increase in BMI.

Results:

By this definition, we replicated 9/13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8/13 SNP associations (5/8 loci) in East Asians, 7/13 (5/8 loci) in African Americans, 6/13 (4/8 loci) in Hispanics, 5/8 in Pacific Islanders (5/8 loci), and 5/9 (4/8 loci) in American Indians.

Conclusion:

Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine‐mapping in large samples is needed to comprehensively explore these loci in diverse populations.     

GUESS-ing Polygenic Associations with Multiple Phenotypes Using a GPU-Based Evolutionary Stochastic Search Algorithm

Genome-wide association studies (GWAS) yielded significant advances in defining the genetic architecture of complex traits and disease. Still, a major hurdle of GWAS is narrowing down multiple genetic associations to a few causal variants for functional studies. This becomes critical in multi-phenotype GWAS where detection and interpretability of complex SNP(s)-trait(s) associations are complicated by complex Linkage Disequilibrium patterns between SNPs and correlation between traits. Here we propose a computationally efficient algorithm (GUESS) to explore complex genetic-association models and maximize genetic variant detection. We integrated our algorithm with a new Bayesian strategy for multi-phenotype analysis to identify the specific contribution of each SNP to different trait combinations and study genetic regulation of lipid metabolism in the Gutenberg Health Study (GHS). Despite the relatively small size of GHS (n = 3,175), when compared with the largest published meta-GWAS (n>100,000), GUESS recovered most of the major associations and was better at refining multi-trait associations than alternative methods. Amongst the new findings provided by GUESS, we revealed a strong association of SORT1 with TG-APOB and LIPC with TG-HDL phenotypic groups, which were overlooked in the larger meta-GWAS and not revealed by competing approaches, associations that we replicated in two independent cohorts. Moreover, we demonstrated the increased power of GUESS over alternative multi-phenotype approaches, both Bayesian and non-Bayesian, in a simulation study that mimics real-case scenarios. We showed that our parallel implementation based on Graphics Processing Units outperforms alternative multi-phenotype methods. Beyond multivariate modelling of multi-phenotypes, our Bayesian model employs a flexible hierarchical prior structure for genetic effects that adapts to any correlation structure of the predictors and increases the power to identify associated variants. This provides a powerful tool for the analysis of diverse genomic features, for instance including gene expression and exome sequencing data, where complex dependencies are present in the predictor space.     

Periatrial Epicardial Fat Is Associated with Markers of Endothelial Dysfunction in Patients with Atrial Fibrillation

Background

Epicardial adipose tissue (EAT) is associated to atrial fibrillation (AF) burden and outcome after AF ablation. We intended to determine whether global or local EAT is associated with systemic and/or left atrial (LA) inflammation and markers of endothelial dysfunction in AF patients.

Methods and Results

Total, atrial, and ventricular EAT volume (EATtotal, EATatrial, EATventricular) were measured by multislice cardiac CT in 49 patients with paroxysmal (PAF, n=25) or persistent AF (PeF, n=24). Periatrial epicardial fat thickness at the esophagus (LA-ESO) and thoracic aorta (LA-ThA) were also measured. Vascular endothelial growth factor (VEGF), interleukin-8 (IL-8), soluble intercellular adhesion molecule 1 (sICAM-1), transforming growth factor-β1 (TGF-β1), and von Willebrand Factor (vWF) levels were measured in peripheral and LA blood samples obtained during catheterization during AF ablation. Patients with PeF had higher EATatrial (P<0.05) and LA-ESO (P=0.04) than patients with PAF. VEGF, IL-8, and TGF-β1 were not associated with EAT. In contrast, after adjusting for LA volume and body mass index, higher LA-ThA was significantly associated with higher sICAM-1 and vWF levels, both in peripheral blood (P<0.05) and in LA (P<0.05). Similar results were found with LA-ESO. Body mass index, EATtotal and EATventricular were not associated with sICAM-1 and vWF.

Conclusions

Periatrial epicardial fat showed a significant positive association with increased levels of sICAM-1 and vWF, which are biomarkers of endothelial dysfunction. No such associations were found when considering body mass index or EATtotal. These results suggest that local EAT rather than regional or total adiposity may modulate endothelial dysfunction in patients with AF.     

Efficient mutation identification in zebrafish by microarray capturing and next generation sequencing

Fish models like medaka, stickleback or zebrafish provide a valuable resource to study vertebrate genes. However, finding genetic variants e.g. mutations in the genome is still arduous. Here we used a combination of microarray capturing and next generation sequencing to identify the affected gene in the mozartkugel^p11cv (mzl^p11cv) mutant zebrafish. We discovered a 31-bp deletion in macf1 demonstrating the potential of this technique to efficiently isolate mutations in a vertebrate genome.     

How SLX4 cuts through the mystery of HIV-1 Vpr-mediated cell cycle arrest

Vpr is one of the most enigmatic viral auxiliary proteins of HIV. During the past twenty years, several activities have been ascribed to this viral protein, but one, its ability to mediate cell cycle arrest at the G2 to M transition has been the most extensively studied. Nonetheless, the genuine role of Vpr and its pathophysiological relevance in the viral life cycle have remained mysterious. Recent work by Laguette et al. (Cell 156:134-145, 2014) provides important insight into the molecular mechanism of Vpr-mediated G2 arrest. This study highlights for the first time how Vpr recruits the SLX4 endonuclease complex and how Vpr-induced inappropriate activation of this complex leads to G2 arrest. Here, we will discuss these findings in the light of previous work to show how they change the view of Vpr’s mechanism of action. We will also discuss how these findings open new questions towards the understanding of the biological function of Vpr regarding innate immune sensing.